Evidence map›Paper›PMID 30165162›Full record

ArticleJournal of the American Academy of Dermatology2019

Clinical spectrum of cutaneous melanoma morphology.

Nikolai Klebanov, Nicole S Gunasekera, William M Lin, Elena B Hawryluk, David M Miller, Bobby Y Reddy, Mitalee P Christman, Derek Beaulieu, Suvithan Rajadurai, Lyn M Duncan and 2 more

Abstract read
In one paragraph

Article in Journal of the American Academy of Dermatology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 33 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Nikolai KlebanovWellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Nicole S GunasekeraWellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
William M LinDepartment of Dermatology, Massachusetts General Hospital, Boston, Massachusetts.
Elena B HawrylukDepartment of Dermatology, Massachusetts General Hospital, Boston, Massachusetts.
David M MillerWellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts; Division of Hematology and Oncology, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Bobby Y ReddyWellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts.
Mitalee P ChristmanWellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Derek BeaulieuWellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Suvithan RajaduraiWellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Lyn M DuncanPathology Service, Massachusetts General Hospital, Boston, Massachusetts.
Arthur J SoberDepartment of Dermatology, Massachusetts General Hospital, Boston, Massachusetts.
Hensin TsaoWellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts. Electronic address: htsao@mgh.harvard.edu.
Massachusetts General Hospital · USHarvard University · US

Funding

Molecular Risk Assessment in Hereditary MelanomaK24CA149202 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI TSAO, HENSIN · 2010 to 2019
$1.9M
NCI NIH HHS K24 CA149202
6 · The paper itself

Abstract

backgroundMelanoma can mimic other cutaneous lesions, but the full spectrum and prevalence of these morphologic variants remain largely unknown.

objectiveTo classify nonacral cutaneous melanomas into distinct morphologic clusters and characterize clusters' clinicopathologic features.

methodsAll pathologic melanoma diagnoses (occurring during 2011-2016) were reviewed for routine prebiopsy digital photographs (n = 400). Six dermatologists independently assigned lesions into 1 of 14 diagnostic classes on the basis of morphology. Image consensus clusters were generated by K-means; clinicopathologic features were compared with analysis of variance and χ

resultsFive morphologic clusters were identified: typical (n = 136), nevus-like (n = 81), amelanotic/nonmelanoma skin cancer (NMSC)-like (n = 70), seborrheic keratosis (SK)-like (n = 68), and lentigo/lentigo maligna (LM)-like (n = 45) melanomas. Nevus-like melanomas were found in younger patients. Nevus-like and lentigo/LM-like melanomas tended to be thinner and more likely identified on routine dermatologic examinations. NMSC-like melanomas were tender, thicker, more mitotically active, and associated with prior NMSC. Typical and SK-like melanomas had similar clinicopathologic features. LIMITATIONS: Cluster subdivision yielded diminished sample sizes. Visual assignment was performed without clinical context.

conclusionWhen primary cutaneous melanomas were assigned into diagnostic groups and subjected to novel consensus clustering, recurrent morphologic patterns emerged. The spectrum of these morphologies was unexpectedly diverse, which might have implications for visual training and possibly clinical diagnosis.

Indexed as

AgedFemaleHumansMaleMelanomaMiddle AgedSkin Neoplasmsdiagnostic accuracyearly diagnosiseducationmelanomamelanoma appearancemelanoma mimicsmorphologynevipigmented lesionsunusual-appearing melanoma

Identifiers

PMID30165162
PMCPMC6492030
OpenAlexW2888845233

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.